Kernels and Distances for Structured Data
Machine Learning
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
The Description Logic Handbook
The Description Logic Handbook
An algorithm based on counterfactuals for concept learning in the Semantic Web
Applied Intelligence
Randomized metric induction and evolutionary conceptual clustering for semantic knowledge bases
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Perspectives of Neural-Symbolic Integration
Perspectives of Neural-Symbolic Integration
Completing description logic knowledge bases using formal concept analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Inductive concept retrieval and query answering with semantic knowledge bases through kernel methods
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Kernel methods for mining instance data in ontologies
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Query answering and ontology population: an inductive approach
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
Foundations of refinement operators for description logics
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Resolution-Based approximate reasoning for OWL DL
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
A declarative kernel for concept descriptions
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
ReduCE: A Reduced Coulomb Energy Network Method for Approximate Classification
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
Connectionist Models for Formal Knowledge Adaptation
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
GeoS '09 Proceedings of the 3rd International Conference on GeoSpatial Semantics
Theory and Practice of Logic Programming
Towards Learning to Rank in Description Logics
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Induction of concepts in web ontologies through terminological decision trees
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part I
Learning to rank individuals in description logics using kernel perceptrons
RR'10 Proceedings of the Fourth international conference on Web reasoning and rule systems
Prediction of class and property assertions on OWL ontologies through evidence combination
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Learning with semantic kernels for clausal knowledge bases
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Induction of robust classifiers for web ontologies through kernel machines
Web Semantics: Science, Services and Agents on the World Wide Web
Data Mining and Knowledge Discovery
ESWC'12 Proceedings of the 9th international conference on The Semantic Web: research and applications
Semantic query answering in digital libraries
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
Concept Induction in Description Logics Using Information-Theoretic Heuristics
International Journal on Semantic Web & Information Systems
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A novel family of parametric language-independent kernel functions defined for individuals within ontologies is presented. They are easily integrated with efficient statistical learning methods for inducing linear classifiers that offer an alternative way to perform classification w.r.t. deductive reasoning. A method for adapting the parameters of the kernel to the knowledge base through stochastic optimization is also proposed. This enables the exploitation of statistical learning in a variety of tasks where an inductive approach may bridge the gaps of the standard methods due the inherent incompleteness of the knowledge bases. In this work, a system integrating the kernels has been tested in experiments on approximate query answering with real ontologies collected from standard repositories.